fix(README): Update instructions to only use kustomize (#1455)

This commit is contained in:
Tommy Li 2024-02-12 16:07:04 -08:00 committed by GitHub
parent b77e6f38d5
commit a9d7df96d2
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 5 additions and 10 deletions

View File

@ -73,17 +73,12 @@ To install the standalone Kubeflow Pipelines V1 with Tekton , run the following
-p '{"data":{"default-timeout-minutes": "0"}}'
```
3. Install Kubeflow Pipelines with Tekton backend (`kfp-tekton`) `v1.9.2` [custom resource definitions](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/)(CRDs).
3. Install Kubeflow Pipelines with Tekton backend (`kfp-tekton`) `v1.9.2` deployment
```shell
kubectl apply --selector kubeflow/crd-install=true -f https://raw.githubusercontent.com/kubeflow/kfp-tekton/master/install/v1.9.2/kfp-tekton.yaml
kubectl apply -k https://github.com/kubeflow/kfp-tekton//manifests/kustomize/env/kfp-template\?ref\=v1.9.2
```
4. Install Kubeflow Pipelines with Tekton backend (`kfp-tekton`) `v1.9.2` deployment
```shell
kubectl apply -f https://raw.githubusercontent.com/kubeflow/kfp-tekton/master/install/v1.9.2/kfp-tekton.yaml
```
5. Then, if you want to expose the Kubeflow Pipelines endpoint outside the cluster, run the following commands:
4. Then, if you want to expose the Kubeflow Pipelines endpoint outside the cluster, run the following commands:
```shell
kubectl patch svc ml-pipeline-ui -n kubeflow -p '{"spec": {"type": "LoadBalancer"}}'
```
@ -93,13 +88,13 @@ To install the standalone Kubeflow Pipelines V1 with Tekton , run the following
kubectl get svc ml-pipeline-ui -n kubeflow -o jsonpath='{.status.loadBalancer.ingress[0].ip}'
```
6. (GPU worker nodes only) If your Kubernetes cluster has a mixture of CPU and GPU worker nodes, it's recommended to disable the Tekton default affinity assistant so that Tekton won't schedule too many CPU workloads on the GPU nodes.
5. (GPU worker nodes only) If your Kubernetes cluster has a mixture of CPU and GPU worker nodes, it's recommended to disable the Tekton default affinity assistant so that Tekton won't schedule too many CPU workloads on the GPU nodes.
```shell
kubectl patch cm feature-flags -n tekton-pipelines \
-p '{"data":{"disable-affinity-assistant": "true"}}'
```
7. (OpenShift only) If you are running the standalone KFP-Tekton on OpenShift, apply the necessary security context constraint below
6. (OpenShift only) If you are running the standalone KFP-Tekton on OpenShift, apply the necessary security context constraint below
```shell
curl -L https://raw.githubusercontent.com/kubeflow/kfp-tekton/master/install/v1.9.2/kfp-tekton.yaml | yq 'del(.spec.template.spec.containers[].securityContext.runAsUser, .spec.template.spec.containers[].securityContext.runAsGroup)' | oc apply -f -
oc apply -k https://github.com/kubeflow/kfp-tekton//manifests/kustomize/third-party/openshift/standalone